| 研究課題/領域番号 |
22KF0305
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| 配分区分 | 基金 |
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| 研究機関 | 九州大学 |
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研究代表者 |
溝口 孝司 九州大学, 比較社会文化研究院, 教授 (80264109)
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| 研究分担者 |
LOFTUS JAMES 九州大学, 比較社会文化研究院, 外国人特別研究員
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| 研究期間 (年度) |
2023-03-08 – 2025-03-31
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| キーワード | Learning strategies / idiosyncratic variance / geometric morhpmetrics / ethnographic comparison / Yayoi period / Kofun period |
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| 研究実績の概要 |
This study aims to provide quantifiable measures of the variable human learning strategies and idiosyncratic variance in prehistoric pottery communities in Japan. Previous international and domestic studies have not accurately quantified learning strategies using complex statistical or 3D methodology, which this study aims to achieve. The study utilizes a newly developed geometric morphometric statistical package in R, along with novel 3D technologies. The Yayoi and Kofun periods in Japan are being compared to modern ethnographic evidence in both Japan and other countries, serving as a case study for this project.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
To date, our exploration into the realm of pottery production has been significantly advanced through the implementation of a groundbreaking 3D visualization method. This innovative approach allows for the meticulous capture of minute variations adorning the surface of pottery. Through this method, we have discerned a myriad of traits that serve as pivotal markers in characterizing the idiosyncratic features of the hand movements intrinsic to the art of pottery production. At the heart of this endeavor lies the quest to unravel the intricacies of hand movements . With our novel 3D visualization technique, we have been able to delve deep into the subtle nuances of these movements, unveiling a wealth of information previously inaccessible through traditional means.
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| 今後の研究の推進方策 |
Expanding on the outlined program involves a deeper exploration of connections between identified traits and pottery production patterns. This includes refining the 3D visualization method to capture more nuanced variations on pottery surfaces, possibly through improved imaging resolution or additional sensors. By enhancing data collection, we can better understand the subtle movements and techniques used by potters. Additionally, correlating identified traits with specific stages of pottery-making can reveal insights into how hand movements evolve throughout production. This understanding illuminates individual preferences, regional influences, and cultural styles, contributing to the reconstruction of the process of transmitting and sharing pottery production technology.
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